Blate, Micah

Micah licensed engineer with 10 years of experience, and serves as Hazen's Northeast Region Biosolids Practice Lead, located in Philadelphia, PA. His experience includes planning, design, process support/ modeling, and optimization of wastewater and biosolids facilities. Additionally, Micah is currently a PhD candidate at Drexel University with research focused in anaerobic digestion, codigestion, anammox, and PFAS degradation.

Titles from this speaker

Description: A New Biosolids Management Trend is Emerging: Biochar Producing Technologies are...

A New Biosolids Management Trend is Emerging: Biochar Producing Technologies are Rising to the Top, Wonder Why?

Abstract

The mounting pressure on land application of biosolids coupled with rising costs of processing, hauling and beneficial use is becoming a burden on utilities. The presence of PFAS and potential regulations for practicing land application require considering emerging technologies with PFAS reduction capabilities. Pyrolysis and gasification are emerging technologies that are gaining interest for biosolids management and in most cases, they are the top alternatives for consideration. This trend is mainly due to significant reduction in mass and volume, thus significant reduction in beneficial use costs making the overall economics favorable when compared to conventional technologies. Pyrolysis and gasification produce biochar that has no detectable PFAS, protecting utilities from any future regulation for biosolids land application. Finally, biochar is considered a carbon sink due to carbon sequestration, thus reducing overall greenhouse gas emissions. This paper presents the results from various evaluations for different utility sizes and geography.

This paper presents results from various biosolids management studies for facilities with different sizes and geography. Emerging technologies that convert biosolids to biochar, such as gasification or pyrolysis, are rising to the top, mainly due to reducing overall cost, ability to beneficially use biochar with non-detect PFAS and finally greenhouse gas emission reduction.

SpeakerAbu-Orf, Mohammad

Presentation time

14:00:00

14:25:00

Session time

13:30:00

15:00:00

SessionUnderstanding and Addressing PFAS in Biosolids

Session locationRoom N426b - Level 4

TopicMunicipal Wastewater Treatment Design, PFAS

Author(s)

Abu-Orf, Mohammed

Author(s)M. Abu-Orf 1; M. Blate 1 ; D. Dursun 2; P. Knowles 3; M. Abu-Orf 1;

Author affiliation(s)Hazen and Sawyer, New York, NY 1; Hazen and Sawyer, New York, NY 1 ; Hazen and Sawyer, New York, NY 2; Hazen and Sawyer, New York, NY 3; Hazen and Sawyer, New York, NY 1;

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Oct 2023

DOI10.2175/193864718825159012

Volume / Issue

Content sourceWEFTEC

Word count18

Description: Collaborative, Trigger-Based Biosolids Masterplan for Seven-Facility Municipality in...

Collaborative, Trigger-Based Biosolids Masterplan for Seven-Facility Municipality in the Chesapeake Bay Watershed

Abstract

The Anne Arundel County Department of Public Works (AACo) owns and operates seven (7) Water Reclamation Facilities (WRF): Annapolis Water Reclamation Facility (AWRF), Broadneck Water Reclamation Facility (BNWRF), Broadwater Water Reclamation Facility (BWWRF), Cox Creek Water Reclamation Facility (CCWRF), Maryland City Water Reclamation Facility (MCWRF), Patuxent Water Reclamation Facility (PWRF), and Piney Orchard Water Reclamation Facility (POWRF). The plants are distributed throughout Anne Arundel County, as shown in Figure 1, and range in size from approximately 1 million gallons per day (mgd) to 15 mgd. AACo maintains a contract with a single full-service provider (FSP) since the early 1990's who manages the entirety of the county's biosolids output. The FSP is responsible for operating the dewatering and Class B alkaline stabilization at AWRF, BNWRF, BWWRF, MCWRF, and PWRF; transporting liquid, unstabilized solids from POWRF to the PWRF; and processing a minimum of 25% of the total volume of unstabilized cake to meet Class A/EQ standards. The Class A/EQ requirement is being met by processing all the solids generated at CCWRF to meet Class A/EQ standards. Class B alkaline-stabilized biosolids are transported to a long-term storage lagoon or to permitted land application sites in Maryland, Virginia, or Pennsylvania. AACo maintains no on-site storage for dewatered cake, requiring off-site transport to storage, beneficial use, or disposal each day dewatering processes operate. To meet the Class A/EQ requirement, unstabilized solids are transported by the FSP to the FSP's Watershed Resource Center for processing via alkaline addition and pasteurization. In the face of current regulatory trends, diminishing end-use outlets, and emerging biosolids treatment technologies a new, holistic approach to managing the County's biosolids is being developed in collaboration between County staff and Hazen and Sawyer. The intent of this project is to develop a long-term biosolids management plan that will address these challenges, and was approached through four unique phases: initiate phase, comprehend phase, explore phase, and converge phase, as shown on Figure 2. 1 - Initiate phase: the project team investigated all of AACo facilities and operational data to understand the existing conditions of each WRF and their operational metrics. Then an end-use market study and regulatory assessment was conducted to build a comprehensive market assessment that would inform the next phase. 2 - Comprehend phase: a set of screening criteria and associated weights were developed, in a collaborative process with all project stakeholders, through a series of stakeholder engagement workshops. The weighted criteria would be subsequently utilized to rank and score biosolids management options against one another. 3 & Explore phase: An evaluation of regionalized and/or centralized location for the biosolids processing alternative. 4 & Converge phase: To maximize flexibility for the County, a trigger-based roadmap was developed that outlined the best possible biosolids management track should one of several no-go criteria be satisfied. To this end, the Masterplan was structured in such a way that a maximum of capital dedicated to a previous management track be shunted to the new, alternate track, that would circumvent (subvert?) the no-go trigger. Hazen and AACo worked and is working collaboratively through the project to develop a long-term solution for AACo. Some of the major challenges AACo faces include: - Large distances between WRFs, as well as locations of WRFs in relation to residential areas limiting the location for a Centralized/regional facility. - Potential long-term unsustainability of land application related to current and future regulatory trends. - Land-application Issues in MD/Chesapeake Bay. The world of options of potential biosolids management alternatives which will be evaluated as part of the project include: Gasification/ pyrolysis, Anaerobic digestion, advanced anaerobic digestion, anaerobic digestion coupled with thermal drying, third-party, composting, and thermal drying. In order to score and rank the alternatives against one another a set of criteria were developed which include: Technical, Economic, Environmental, and Social. A weight is assigned, as determined by AACo, to each criteria to allow for scoring and ranking. To address regionalization, a multi-facility tool has been developed. The tool is capable of tracking solids from various plants to singular or multiple outlets while also varying the type of treatment alternatives. The tool also tracks green house gas emissions and costs, providing a user-friendly dashboard of the findings. Additionally, a tool is being developed which will serve as a digital twin of the selected alternative. The digital twin will be capable of tracking energy and solids through a user-friendly dashboard. The project will be complete by the time of the presentation and will be presented by both AACo and Hazen. The presentation will provide a clear, concise path for master planning for utilities with multiple facilities.

This paper was presented at the WEF Residuals and Biosolids Conference in Columbus, Ohio, May 24-27, 2022.

SpeakerBlate, Micah

Presentation time

14:30:00

15:00:00

Session time

13:30:00

17:00:00

Session number02

Session locationGreater Columbus Convention Center, Columbus, Ohio

TopicMaster Planning, Regionalization, Strategic Plan

Author(s)

M. Blate

Author(s)M. Blate1; A. Thomas2; J. Howard3; C. Saunders4; C. Portner5

Author affiliation(s)Residuals and Biosolids Speaker; 1Residuals and Biosolids Speaker; 2Residuals and Biosolids Speaker; 3Anne Arundel County DPW; 4Hazen and Sawyer; 5

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date May 2022

DOI10.2175/193864718825158434

Volume / Issue

Content sourceResiduals and Biosolids

Word count13

Cost of Removing PFAS from WRRF Effluent and Biosolids

Abstract

This study developed capital and operation and maintenance (O&M) cost estimates and curves to remove and destroy per- and polyfluoroalkyl substances (PFAS) from municipal water resource recovery facility (WRRF) effluent and biosolids. Class 5 cost estimates (-30%/+50%) for the assumed design bases were estimated based on vendor quotes and standard design practices for combinations of technologies pre-screened to be both commercially applied and effective at PFAS separation and/or destruction. Three treatment alternatives were developed for 0.1 to 10 MGD of tertiary treated WRRF effluent and two treatment alternatives were developed for 1.0 to 10 dry tons per day (dtpd) of dewatered WRRF biosolids. Estimated costs for a 10 MGD facility producing 10 dptd biosolids are approximately $79 to $250 million in capital costs and $50 to $20 million in annual operating costs, including consideration of all alternatives developed. Cost per mass of targeted PFAS removed (7 compounds for WRRF effluent and 9 compounds for WRRF biosolids) ranged from $370,000 per pound of PFAS removed from a 50 dptd WRRF biosolids treatment facility to $8 million per pound of PFAS removed from a 0.1 MGD WRRF effluent treatment facility. These costs do not include any retrofits needed to add tertiary treatment upstream of PFAS separation processes for WRRF effluent or to achieve 15%-25% solids content prior to PFAS destruction processes for WRRF biosolids.

This study developed capital and O&M cost estimates to remove and destroy per- and polyfluoroalkyl substances (PFAS) from municipal water resource recovery facility (WRRF) tertiary effluent and dewatered biosolids. Estimated costs for a 10 MGD/10 dtpd facility are approximately $79 to $250 million in capital costs and $50 to $20 million in annual operating costs. 20-year costs per mass of PFAS removed ranged from $370,000 per pound to $8 million per pound of PFAS removed.

SpeakerLing, Alison

Presentation time

16:30:00

17:00:00

Session time

15:30:00

17:00:00

SessionPFAS Impacted WRFs: Knowledge Update

Session locationRoom S401d - Level 4

TopicDisinfection and Public Health, Intermediate Level, PFAS, Research and Innovation, Utility Management and Leadership

Author(s)

Ling, Alison

Author(s)A. Ling 1; B. Vermace 2 ; A. McCabe 3; K. Wolohan 4; D. Dursun 5; M. Blate 6; M. Abu-Orf 6; S. Kyser 7; A. Ling 1;

Author affiliation(s)Department of Civil Engineering, University of St. Thomas 1; Barr Engineering Company 2 ; Barr Engineering Company 3; Barr Engineering Company 4; Hazen and Sawyer 5; Hazen and Sawyer 6; Hazen and Sawyer 6; Minnesota Pollution Control Agency 7; Department of Civil Engineering, University of St. Thomas 1;

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Oct 2023

DOI10.2175/193864718825159129

Volume / Issue

Content sourceWEFTEC

Word count10

Exciting Applications of Machine Learning in the Water Industry

Abstract

Two applications of machine learning (ML) in the water space were developed to illustrate the power of these tools: 1) A fully deployed model predicting influent wastewater flow for wet weather management. 2) A desktop model predicting the percent total solids (%TS) in cake on any given day. Both of these ML models provide operational staff with insight that could not be generated through other means (i.e., mechanistic models) by virtue of the way the machine learning algorithms look for explanatory variables.

SpeakerBlate, Micah

Presentation time

13:30:00

13:50:00

Session time

13:30:00

15:00:00

SessionData-Driven Engineering through Data Analytics

Session number303

TopicFacility Operations and Maintenance, Intelligent Water, Resilience, Disaster Planning and Recovery

Author(s)

Micah Blate

Author(s)E. Bailey4; D. Dursun3; K. Bilyk2; M.D. Blate1;

Author affiliation(s)Hazen and Sawyer, Philadelphia, PA1Hazen and Sawyer, Raleigh, NC2Hazen and Sawyer, San Diego, CA3Raleigh Water, Raleigh, NC4

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Oct 2021

DOI10.2175/193864718825158047

Volume / Issue

Content sourceWEFTEC

Word count10

Machine Learning for Dewatering Optimization

Abstract

The water industry is beginning to recognize and apply machine learning (ML) as a tool to optimize system operations in a way that was not possible even a few years ago. This is primarily due to advances in online instrumentation, data management and Cloud computing. At its simplest, ML is learning from data. Every day, various types of data are recorded on a massive scale throughout the water industry, and ML can be used to analyze these complex datasets, helping operators by leveraging the objective and powerful capabilities of computers to identify and utilize patterns from the data that a human may not recognize. Machine learning models are developed through model training, after which they are used to make predictions on 'unseen data' & real-time data that will be brought into the model to provide knowledge or insights for decision-making. Well-trained (or calibrated) models can explore and process massive datasets in real time while also providing extremely rapid predictions, insights, and/or recommendations for operators-a difficult and sometimes impossible task for a human, especially in a short time frame. That said, data-driven ML tools are meant to assist and not replace human intelligence, and they do not have to be complicated or involve massive amounts of data to be useful. Operational experience and expertise, rather, is fundamental to successful ML development, interpretation, and implementation. The use of water experts to develop an ML model is critical for integrating the science of water into the model. Once in production, it will always be important for a human to review the recommendations of the model, periodically verify the model is continuously learning, and apply their own judgment and experience to the question at hand. One of the most compelling benefits of building ML models is that is allows the user to always have an up-to-date model of their system. This differs from most mechanistic modeling software packages that must be recalibrated by a human every couple of years and that likely have significant drift during that time period (e.g., biological process simulators, collection system models). In addition, ML models can account for some real-life complexity and nuances that may not be captured in mechanistic models (e.g., biological phosphorus modeling is often a simplified version of reality). This presentation will describe two applications of ML in the water space-one a fully deployed model predicting influent wastewater flow for wet weather management, and the second a desktop model predicting the percent total solids (%TS) in cake on any given day. Cake %TS Predictor We endeavored to determine if we could develop an empirical relationship between explanatory variables and dewaterability. The value propositions are that (1) enhanced understanding of the variables contributing to improved dewaterability allows the user to operate optimally to reduce hauling and disposal costs, and (2) polymer dose could be increased to assist on days with poor dewaterability. Five years of data from a plant averaging 22% cake with an average polymer dose of 42 lb/DT was used for training. Seven explanatory variables including the influent carbon to nitrogen ratio times ash content (C/N*ash) were used to predict %TS with a precision of +/- 0.4 %. Two separate models were generated to gain better insight into how the explanatory variables affect dewaterability. For example, both showed a positive correlation between increased C/N*ash and %TS in cake as other studies have shown (CNash & A novel parameter predicting cake solids of dewatered digestates, O.K. Svennevik et al. / Water Research 158 (2019) 350-358). Figure 1 compares the predicted and observed results. These models concluded that only 20 percent of the factors influencing dewatering are truly fixed properties, meaning the remainder are operational variables that could be modified to optimize dewaterability. Work is ongoing to better understand how these insights generated from ML compliment the ongoing mechanistic research in this area, and to see if deployment is of interest at any utilities.

This paper was presented at the WEF Residuals and Biosolids Conference in Columbus, Ohio, May 24-27, 2022.

SpeakerBlate, Micah

Presentation time

13:30:00

14:00:00

Session time

13:30:00

16:45:00

Session number14

Session locationGreater Columbus Convention Center, Columbus, Ohio

TopicDewaterability, Dewatering Optimization, Machine Learning

Author(s)

M. Blate

Author(s)M. Blate1; D. Dursun2; K. Bilyk3

Author affiliation(s)Residuals and Biosolids Speaker; 1Hazen and Sawyer; 2Hazen and Sawyer; 3

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date May 2022

DOI10.2175/193864718825158418

Volume / Issue

Content sourceResiduals and Biosolids

Word count6

Description: WRF Project# 5307: Evaluation of Source Separated Organic Feedstock Pretreatment and...

WRF Project# 5307: Evaluation of Source Separated Organic Feedstock Pretreatment and Management Practices

Abstract

INTRODUCTION This paper will provide the project approach and results for Water Research Foundation (WRF) Project# 5037 Evaluation of Source Separated Organic (SSO) Feedstock Pretreatment and Management Practices. The final report is scheduled for release in summer of 2022. SSO co-digestion with wastewater solids at Water Resource Recovery Facilities (WRRFs) offers promise to advance sustainability through beneficial reuse of the organic fraction of pre- and post-consumer waste streams (source separated organics), which would otherwise be disposed in landfills. Promoting SSO diversion from landfills to anaerobic digestion (AD) is predicated on SSO feedstock pretreatment to enhance the digestibility and conveyance of SSOs. This project, as funded by the Water Research Foundation, aims to comprehensively evaluate SSO pretreatment technologies with guidance from existing facilities to develop recommendations for SSO pre-treatment alternatives for utilities considering SSO diversion. The project has been divided into four tasks: 1.Task 1: Global Literature Review and Survey of Existing Technologies and Management Strategies 2.Task 2: Evaluation of Existing Technologies and Management Strategies 3.Task 3: Case Studies with a Wastewater Industry Focus 4.Task 4: SSO Pretreatment Analysis and Decision Tool This project provides guidance for utilities interested in SSO pre-treatment and co-digestion in order to: 1. Successfully build new or enhance existing SSO pretreatment and co-digestion programs, 2. Address challenges and opportunities involved with SSO pretreatment, 3. Identify SSO pretreatment requirements based on SSO feedstock quality and quantity, an 4.Determine capital and O&M costs and potential impacts on WRRFs. This Report will be published January 2023. APPROACH Information pertaining to SSO pretreatment was gathered from literature sources including conference proceedings, project reports, journal articles, and manufacturer documentation in conjunction with questionaries from utility and vendor partners, as well as case studies from domestic and international facilities. Using a four-task approach, information has been distilled into a literature review, fact sheets, case studies, and a SSO pre-treatment guidance tool. Further, this information has been compiled into a PowerBI dashboard. The compatibility and effectiveness of multiple SSO pretreatment technologies were evaluated with information gathered from currently operating facilities which informed the development of SSO pretreatment selection workflows. These workflows were constructed based on contaminant properties such as size and type to distinguish appropriate pretreatment technology selection. RESULTS AND FINDINGS Task 1. Global Literature Review Task 1 focused on gathering information related to the application of SSO pretreatment prior to AD which was assembled in a literature review. Results from the literature review were organized by features and capabilities of unit operations and processes (UOPs). Physical UOPs were the most frequently implemented SSO pretreatment technologies used for both initial and polishing steps as shown in Figure 1. In addition, package units were found to be very attractive for utilities seeking multiple technologies in series for efficient removal of numerous contaminants. A thorough list of pretreatment technology vendors was also provided as a reference for utilities planning pretreatment installations. Task 2. Existing Technologies and Management Strategies Evaluation Seventeen (17) utilities and technology providers, both in the US and abroad, were surveyed through the completion of a questionnaire inquiring about existing pretreatment facilities. The information gathered was summarized into factsheets (example shown in Figure 2) containing information such as process flow diagrams, facility details, lessons learned, and maintenance requirements. Major findings from Task 2 include: -Receiving pre-treated SSO is advantageous for controlling consistency and material quality. -Adequate storage should be provided at the receiving facility. -Removing contamination to the extent possible ensures that downstream equipment and digester(s) aren't adversely impacted by SSO. -Storing critical spare parts on site is recommended. Task 3. Case Studies Results Task 3 results contain insight from seven case studies focused on SSO pretreatment in the wastewater industry. Case studies provided detailed information related to each utility such as mass balances, facility financial information, construction characteristics, and anticipated maintenance schedules. Unit cost curves have been developed for the SSO pretreatment facilities (example shown in Figure 3) to provide an estimate of construction cost, O&M cost, biogas revenue, tipping fees, and inert disposal costs as a function of wet ton of waste. Overall, increasing facility size had decreasing unit costs due to economies of scale. Task 4. SSO Pretreatment Selection Guidance Much of the technology documentation accumulated through the literature review, database development, and case studies was instrumental in the development of multiple SSO pretreatment workflows to guide SSO pretreatment selection. Workflows created as part of Task 4 are structured by contaminant type, size, and physiochemical properties. For example, as shown in Figure 4, appropriate selection of metal and glass removal technologies is contingent on the material size and can be further distinguished by color, magnetism, mobility. DISCUSSION AND BENEFITS The collection of information provided in this study is vital for utilities considering SSO pretreatment by providing technology descriptions, financial information, process mass balances, and selection tools for utilities to functionally apply SSO pretreatment at existing or future anaerobic digestors. While previous studies have focused on AD optimization, there is limited information related to the nuances of SSO pretreatment operation and overall pretreatment effectiveness as discussed in this study. As facilities continue to push for more sustainable waste solutions, the application of SSO pretreatment technologies can be a cost-effective improvement in AD performance.

This paper was presented at the WEF/IWA Residuals and Biosolids Conference, May 16-19, 2023.

SpeakerBlate, Micah

Presentation time

16:15:00

16:45:00

Session time

13:30:00

16:45:00

SessionSession 14: Co-Digestion

Session number14

Session locationCharlotte Convention Center, Charlotte, North Carolina, USA

TopicCase Studies/Lessons Learned

Author(s)

M. Blate

Author(s)M. Blate1, M. Abu-Orf2, D. Dursun3, K. Landry4, C. Murray5, R. Sharp6,

Author affiliation(s)Hazen and Sawyer1; Manhattan College2

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date May 2023

DOI10.2175/193864718825158867

Volume / Issue

Content sourceResiduals and Biosolids

Word count14

WRF Project# 5307: Evaluation of Source Separated Organic Feedstock Pretreatment and Management Practices

Abstract

INTRODUCTION
This paper will provide the project approach and results for Water Research Foundation (WRF) Project# 5037 Evaluation of Source Separated Organic (SSO) Feedstock Pretreatment and Management Practices. The final report is scheduled for release in summer of 2022. SSO co-digestion with wastewater solids at Water Resource Recovery Facilities (WRRFs) offers promise to advance sustainability through beneficial reuse of the organic fraction of pre- and post-consumer waste streams (source separated organics), which would otherwise be disposed in landfills. Promoting SSO diversion from landfills to anaerobic digestion (AD) is predicated on SSO feedstock pretreatment to enhance the digestibility and conveyance of SSOs. This project, as funded by the Water Research Foundation, aims to comprehensively evaluate SSO pretreatment technologies with guidance from existing facilities to develop recommendations for SSO pre-treatment alternatives for utilities considering SSO diversion. The project has been divided into four tasks: 1. Task 1: Global Literature Review and Survey of Existing Technologies and Management Strategies 2. Task 2: Evaluation of Existing Technologies and Management Strategies 3. Task 3: Case Studies with a Wastewater Industry Focus 4. Task 4: SSO Pretreatment Analysis and Decision Tool This project provides guidance for utilities interested in SSO pre-treatment and co-digestion in order to: 1. Successfully build new or enhance existing SSO pretreatment and co-digestion programs, 2. Address challenges and opportunities involved with SSO pretreatment, 3. Identify SSO pretreatment requirements based on SSO feedstock quality and quantity, an 4. Determine capital and O&M costs and potential impacts on WRRFs. APPROACH Information pertaining to SSO pretreatment was gathered from literature sources including conference proceedings, project reports, journal articles, and manufacturer documentation in conjunction with questionaries from utility and vendor partners, as well as case studies from domestic and international facilities. Using a four-task approach, information has been distilled into a literature review, fact sheets, case studies, and a SSO pre-treatment guidance tool. Further, this information has been compiled into a PowerBI dashboard. The compatibility and effectiveness of multiple SSO pretreatment technologies were evaluated with information gathered from currently operating facilities which informed the development of SSO pretreatment selection workflows. These workflows were constructed based on contaminant properties such as size and type to distinguish appropriate pretreatment technology selection.
RESULTS AND FINDINGS
Task 1. Global Literature Review Task 1 focused on gathering information related to the application of SSO pretreatment prior to AD which was assembled in a literature review. Results from the literature review were organized by features and capabilities of unit operations and processes (UOPs). Physical UOPs were the most frequently implemented SSO pretreatment technologies used for both initial and polishing steps as shown in Figure 1. In addition, package units were found to be very attractive for utilities seeking multiple technologies in series for efficient removal of numerous contaminants. A thorough list of pretreatment technology vendors was also provided as a reference for utilities planning pretreatment installations.
Task 2. Existing Technologies and Management Strategies Evaluation Seventeen (17) utilities and technology providers, both in the US and abroad, were surveyed through the completion of a questionnaire inquiring about existing pretreatment facilities. The information gathered was summarized into factsheets (example shown in Figure 2) containing information such as process flow diagrams, facility details, lessons learned, and maintenance requirements. Major findings from Task 2 include: - Receiving pre-treated SSO is advantageous for controlling consistency and material quality. - Adequate storage should be provided at the receiving facility. - Removing contamination to the extent possible ensures that downstream equipment and digester(s) aren't adversely impacted by SSO. - Storing critical spare parts on site is recommended.
Task 3. Case Studies Results Task 3 results contain insight from seven case studies focused on SSO pretreatment in the wastewater industry. Case studies provided detailed information related to each utility such as mass balances, facility financial information, construction characteristics, and anticipated maintenance schedules. Unit cost curves have been developed for the SSO pretreatment facilities (example shown in Figure 3) to provide an estimate of construction cost, O&M cost, biogas revenue, tipping fees, and inert disposal costs as a function of wet ton of waste. Overall, increasing facility size had decreasing unit costs due to economies of scale.
Task 4. SSO Pretreatment Selection Guidance Much of the technology documentation accumulated through the literature review, database development, and case studies was instrumental in the development of multiple SSO pretreatment workflows to guide SSO pretreatment selection. Workflows created as part of Task 4 are structured by contaminant type, size, and physiochemical properties. For example, as shown in Figure 4, appropriate selection of metal and glass removal technologies is contingent on the material size and can be further distinguished by color, magnetism, mobility.
DISCUSSION AND BENEFITS
The collection of information provided in this study is vital for utilities considering SSO pretreatment by providing technology descriptions, financial information, process mass balances, and selection tools for utilities to functionally apply SSO pretreatment at existing or future anaerobic digestors. While previous studies have focused on AD optimization, there is limited information related to the nuances of SSO pretreatment operation and overall pretreatment effectiveness as discussed in this study. As facilities continue to push for more sustainable waste solutions, the application of SSO pretreatment technologies can be a cost-effective improvement in AD performance.

This project, as funded by the Water Research Foundation, aims to comprehensively evaluate SSO pretreatment technologies with guidance from existing facilities to develop recommendations for SSO pre-treatment alternatives for utilities considering SSO diversion. A comprehensive evaluation of SSO pretreatment technologies was provided in this study to demonstrate the compatibility and effectiveness of numerous pretreatment technologies as implemented in case studies worldwide.

SpeakerBlate, Micah

Presentation time

13:35:00

13:45:00

Session time

13:30:00

15:00:00

TopicIntermediate Level, Biosolids and Residuals, Energy Production, Conservation, and Management, Research and Innovation

Author(s)

Blate, Micah

Author(s)Micah Blate1; Mohammad Abu-Orf1; Derya Dursun1; Kelly Landry1; Conner Murray1; Nicole Kaiser2; Robert Sharp2

Author affiliation(s)Hazen and Sawyer1; Manhattan College2